Many biological functions are accomplished by altering the expression of various genes through transcriptional (e.g. through control of initiation, provision of RNA precursors, RNA processing, etc.) and/or translational control. For example, fundamental biological processes such as cell cycle, cell differentiation and cell death, are often characterized by the variations in the expression levels of groups of genes.
Gene expression is also associated with pathogenesis. For example, the lack of sufficient expression of functional tumor suppressor genes and/or the over expression of oncogene/protooncogenes could lead to tumorgenesis (Marshall, Cell, 64: 313-326 (1991); Weinberg, Science, 254: 1138-1146 (1991), incorporated herein by reference for all purposes). Thus, changes in the expression levels of particular genes (e.g. oncogenes or tumor suppressors) serve as signposts for the presence and progression of various diseases.
The study of gene expression in the art has been generally concentrated on the regulatory regions of the gene of interest and on the relationships among a few genes. A number of transcriptional factors/DNA binding proteins have been identified and a limited number of regulatory pathways have been discovered. However, the expression of a particular gene is frequently regulated by the expression of a large number of other genes. The expression of those regulatory genes may also be under the control of additional genes. This complex regulatory relationship among genes constitutes a genetic network. The function and regulation of a particular gene can be best understood in the context of this genetic network. As the Human Genome Project and commercial genome research progress at a great rate, most, if not all, of the expressed genes will be partially sequenced in the near future. Understanding the functions and regulatory relationships among the large number of genes is becoming a difficult task with traditional tools. Therefore, there is a need in the art to develop a systematic approach to understand the complex regulatory relationships among large numbers of genes.